Predicting Recurrent Venous Thromboembolism in Patients With Deep-Vein Thrombosis: Development and Internal Validation of a Potential New Prediction Model (Continu-8)

M. Nagler*, S.M.J. Van Kuijk, H. Ten Cate, M.H. Prins, A.J. Ten Cate-Hoek

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Web of Science)


Background: Previous prediction models for recurrent thromboembolism (VTE) are often complicated to apply and have not been implemented widely.Aim: To develop and internally validate a potential new prediction model for recurrent VTE that can be used without stopping anticoagulant treatment for D-dimer measurements in patients with provoked and unprovoked DVT.Methods: Cohort data of 479 patients treated in a clinical care pathway at Maastricht University Medical Center were used. Predictors for the Cox proportional hazards model (unprovoked DVT, male gender, factor VIII levels) were derived from literature and using forward selection procedure. The scoring rule was internally validated using bootstrapping techniques and the predictive ability was compared to existing prediction models.Results: Patients were followed for a median of 3.12 years after stopping anticoagulation treatment (IQR 0.78, 3.90). Sixty-four of 479 patients developed recurrent VTE (13%). The scoring rule consisted of unprovoked DVT (yes: 2 points), male sex (yes: 1 point), and factor VIII > 213 % (yes: 2 points) and was categorized into three groups [i.e., low risk (score 0), medium risk (scores 1, 2, or 3) and high risk (scores 4 and 5)]. The concordance statistic was 0.68 (95% CI: 0.61, 0.75).Conclusion: The discriminative ability of the new Continu-8 score was adequate. Future studies shall verify this score in an independent setting without stopping anticoagulation treatment.
Original languageEnglish
Article number655226
Number of pages8
JournalFrontiers in cardiovascular medicine
Publication statusPublished - 6 Apr 2021


  • venous thrombosis
  • epidemiology
  • therapy
  • mortality
  • risk factors
  • clinical decision making
  • health services research

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